Model releases are exciting when they establish a new frontier on pareto efficiency between cost, intelligence, and speed.
GLM 5.2 and DeepSeek Flash V4 represent the current pareto frontier for intelligence vs. cost, with very reasonable speed to boot.
This release of Gemma 4 on Cerebras at 1.8k tok/sec likely establishes a new pareto frontier for speed vs cost. (Unfortunately I couldn’t find the pricing to verify cost, but it’s a reasonable assumption for this model.)
Why do I find this so exciting?
I believe that effective utilization of speed-cost frontier models is fundamentally a harness engineering problem. Access to ‘instant coding’ is a huge unlock. Intelligence-frontier models can one-shot most tasks, but are modern speed-frontier models lacking any essential capacity for the same functionality? I believe that no, they are not, and that harness engineering can establish a new pareto frontier for highly intelligent, instantaneous models too cheap to meter. Instantaneous responses completely change the dynamic and meta for coding with AI.
GLM 5.2 and DeepSeek Flash V4 represent the current pareto frontier for intelligence vs. cost, with very reasonable speed to boot.
This release of Gemma 4 on Cerebras at 1.8k tok/sec likely establishes a new pareto frontier for speed vs cost. (Unfortunately I couldn’t find the pricing to verify cost, but it’s a reasonable assumption for this model.)
Why do I find this so exciting?
I believe that effective utilization of speed-cost frontier models is fundamentally a harness engineering problem. Access to ‘instant coding’ is a huge unlock. Intelligence-frontier models can one-shot most tasks, but are modern speed-frontier models lacking any essential capacity for the same functionality? I believe that no, they are not, and that harness engineering can establish a new pareto frontier for highly intelligent, instantaneous models too cheap to meter. Instantaneous responses completely change the dynamic and meta for coding with AI.